Pith. sign in

REVIEW 1 cited by

Treatment heterogeneity with right-censored outcomes using grf

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2312.02482 v3 pith:L4ZK5QB6 submitted 2023-12-05 stat.CO stat.APstat.ME

classification stat.COstat.APstat.ME
keywords outcomesright-censoredtreatmentarticleatheyaveragecatescausal
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

This article walks through how to estimate conditional average treatment effects (CATEs) with right-censored time-to-event outcomes using the function causal_survival_forest (Cui et al., 2023) in the R package grf (Athey et al., 2019, Tibshirani et al., 2024) using data from the National Job Training Partnership Act.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. CAST: Time-Varying Treatment Effects with Application to Chemotherapy and Radiotherapy on Head and Neck Squamous Cell Carcinoma

    cs.LG 2025-05 conditional novelty 4.0 of 10

    CAST fits quadratic and spline curves through ten horizon-specific causal forest estimates, reporting a chemotherapy survival benefit in 2,651 head and neck cancer patients that peaks between 50 and 65 months and then...

Pith tools